Title
Iterative blind deconvolution and its application in characterization of eddy current NDE signals
Degree Type
Thesis
Date of Award
2001
Degree Name
Master of Science
Department
Electrical and Computer Engineering
First Advisor
Lalita Udpa
Abstract
Eddy current techniques are widely used to detect and characterize the defects in steam generator tubes in nuclear power plants. Although defect characterization is crucial for the successful inspection of defects, it is often difficult due to due to the finite size of the probes used for inspection. A feasible solution is to model the defect data as the convolution of the defect surface profile and the probe response. Therefore deconvolution algorithms can be used to remove the effect of probe on the signal.
This thesis presents a method using iterative blind deconvolution algorithm based on the Richardson-Lucy algorithm to address the defect characterization problem. Another iterative blind deconvolution method based on Wiener filtering is used to compare the performance. A preprocessing algorithm is introduced to remove the noise and thus enhance the performance. Two new convergence criterions are proposed to solve the convergence problem. Different types of initial estimate of the PSF are used and their impacts on the performance are compared. The results of applying this method to the synthetic data, the calibration data and the field data are presented.
DOI
https://doi.org/10.31274/rtd-180813-5485
Publisher
Digital Repository @ Iowa State University, http://lib.dr.iastate.edu
Copyright Owner
Xiang Cai
Copyright Date
2001
Language
en
Date Available
June 10, 2013
File Format
application/pdf
File Size
122 pages
Recommended Citation
Cai, Xiang, "Iterative blind deconvolution and its application in characterization of eddy current NDE signals" (2001). Retrospective Theses and Dissertations. 113.
https://lib.dr.iastate.edu/rtd/113